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cs.LG2026
Vision-Language-Action Jump-Starting for Reinforcement Learning Robotic Agents
Angelo Moroncelli, Roberto Zanetti, Marco Maccarini +1
Reinforcement learning (RL) enables high-frequency, closed-loop control for robotic manipulation, but scaling to long-horizon tasks with sparse or imperfect rewards remains difficu…
cs.LG2026
Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics
Angelo Moroncelli, Matteo Rufolo, Gunes Cagin Aydin +2
Accurate modeling of robot dynamics is essential for model-based control, yet remains challenging under distributional shifts and real-time constraints. In this work, we formulate…